Wireless communications systems are used to satisfy a variety of mobile voice and data communication needs. Currently, there is demand for additional wireless capabilities so that customers can expand their use of wireless communication devices. This demand is forcing wireless service providers to expand their networks at a rapid rate. The mobility of wireless communication users complicates the deployment of additional network infrastructure such as base stations.
Wireless networks are complex because the infrastructure is often spread over large geographic regions, wireless signals are attenuated as a function of distance, and wireless traffic is not evenly distributed over the served region (e.g. wireless traffic is often clustered into defined areas such as along roadways). Network engineers model wireless networks before deploying system hardware to ensure complete signal coverage and adequate channel capacity. Currently, computer based planning tools are used to perform the complex computations necessary for modelling a wireless network. These models use digitized map databases, geographic coordinates, terrain data, and feature data in an attempt to account for important design constraints. However, the use of digitized map databases undesirably limits the accuracy of computerized network planning.
Since digital maps represent sampled data, there is a spacing between adjacent sample points. The area between each sample point is referred to as a map pixel. The size of each map pixel varies based on the sample spacing used. For example, the area of each map pixel is approximately 90 meters north-south by 70 meters east-west for a 3 arc second USGS map, which is normally used for wireless network planning. Current planning tools use the map pixel as the smallest unit of reference; therefore, features smaller than a map pixel in one dimension are not accurately interpreted. Several types of features used in wireless network planning are smaller than a map pixel in one dimension. Accurately modelling the distance to these features is desirable. Features smaller than a map pixel in one dimension are normally referred to as vectors, with roads and county boundaries being among the most common vector types encountered in wireless network planning.
FIG. 1 illustrates a road 104 traversing map pixels 102. The shaded pixels indicate how the road is perceived after it is rasterized. It can be seen in FIG. 1 that the road value is attributed to the entire pixel even though the road only touches a portion of the pixel. Attributing the road attribute to the entire pixel introduces errors. The errors introduced by using map pixels as the smallest measurement unit are especially problematic when performing propagation loss calculations to points located along a vector. For example, if a car is on a narrow road running through the middle of a map pixel, a propagation calculation to the road can only be computed to an edge of the map pixel containing the road. In addition, other information such as elevation and land-use-land-cover (LULC) are averaged across the entire map pixel, further introducing errors. Thus, the road 104 is not modeled accurately enough to achieve optimum results.
Therefore, a need exists for more accurately computing distances to points along vectors when performing network planning. Furthermore, computing the distance to vector features should not overly burden data storage systems by generating excessive data points.